Prior art methods that implement policy for computer systems that are homogenous in architecture assigned work on a platform specific basis or an operating system basis. For example, the IBM S/390 workload manager uses 390 system platform specific statistics, such as, multi-programming level, virtual storage, expanded storage, to make decisions on where to place work. Prior art methods of policy management have required advance knowledge of how much CPU time or memory an application needs to run to efficiently assign the application in a cluster of computers and take advantage of the cluster resources. Prior art methods of policy management also have created an affinity between certain types of work and a specific computer.
Statistics used by prior art policy management methods have been updated on a periodic basis, whether or not new values have been received. This updating has been scheduled by a timer that signals the update times. This causes additional path length, CPU cycles and concerns about recovery, such as, failure of the timer to signal.
With the advent of computer networks and the distribution of work among the computers, there is a need for a policy manager that can manage policy independent of the architecture of the computers connected in the network.
There is also a need for a method and system for aging statistics that are used in the policy management process.